Interaction potentials used in particle simulations are typically written as a sum of terms which depend on just a few relative particle positions. Traditional simulation methods move all particles at each time step, and may thus spend a lot of time updating inter-particle forces.
We introduce a general, theoretically-grounded method to speed up particle simulations that we call ARPS: Adaptively Restrained Particle Simulations. This method adaptively switches on and off positional degrees of freedom, while letting momenta evolve. We illustrate ARPS on several numerical experiments
The first example is a collision cascade example that demonstrates how ARPS make it possible to smoothly trade between precision and speed.
Precisely, a particle is launched towards a initially static 2D system, and the collision cascade is simulated, first with a traditional particle simulation approach, then with adaptively restrained (AR) particles simulations at different precision thresholds. AR simulations make it possible to smoothly trade between precision and cost, reaching a 10 times speed-up while preserving the major features of the shock.
The second example is a polymer-in-solvent study that shows how one may efficiently compute static equilibrium properties with ARPS.
Precisely, the goal is to compute the hydrodynamic radius of the solvated polymer. For any target precision, restraining solvent particles makes it possible to determine the hydrodynamic radius about four times faster than traditional simulations.
ARPS is introduced in the following paper :
S. Artemova and S. Redon. “Adaptively Restrained Particle Simulations”. Physical Review Letters. Volume 109. Issue 19, p. 190201. Paper. Supplementary material.